In the previous report we described our model for T2D pathogenesis. It builds on the foundational model (Topp et al, J. Theor. Biol. 2000; 206(4):605-19), which posited that moderate but persistent increases in blood sugar mediate negative feedback to increase insulin secretion by increasing beta-cell mass, either by increased replication or reduced apoptosis. However, if that increase fails to occur or is inadequate to restore normal glucose homeostasis, further increases in glucose raise it to a level where it becomes toxic to beta cells. Instead of negative feedback, there is then positive feedback, which causes a catastrophic loss of beta-cell mass and T2D. In addition to quantitative refinements to more accurately reflect the measured dynamics of T2D progression in humans and rodents, we added regulation of beta-cell function, in two distinct forms, in addition to mass. Data show that such changes are more rapid and more extensive than changes in mass, especially for humans, for whom beta-cell replication is very slow after adolescence. The model captures many key features of T2D progression, including the sudden deterioration of glucose control after a long period of gradual worsening (threshold behavior) and the fact that prevention is generally much easier than reversal, but drastic interventions, such as bariatric surgery and extreme caloric restriction can reverse established disease. The model has been further extended to track fasting and post-prandial glucose, rather than just average daily glucose, which is important because individuals differ in which aspect of glucose deviates first from normal. In addition, the model can be paused at any point during progression over years to simulate glucose tolerance tests, both oral (OGTT) and intravenous (IVGTT). One prediction arising from the OGTT simulations is that time to peak glucose is a leading indicator of T2D risk, independent of the conventional fasting and two-hour glucose concentrations. A delayed peak, which is generally a higher peak as well, is indicative of delayed insulin secretion, due to impaired delivery of new insulin granules to the plasma membrane of the beta cells. This prediction was tested by clinical colleagues Sumner and Chung using data from the Federal Women's Study (Publication #1). The work was also highlighted in a press release from the 2017 meeting of The Endocrine Society (http://www.endocrine.org/news-room/current-press-releases/new-simple-tool-can-help-identify-people-at-high-risk-for-prediabetes). They found that time to peak was a statistically independent predictor of T2D status cross-sectionally. This finding needs to be checked in other cohorts. The model predicts that delay of time to peak will be seen longitudinally: the peak should shift to the right as individuals progress. This prediction remains to be tested clinically. Another finding from model simulations is that hemoglobin A1C, which tracks average daily glucose, should be correlated with glucose excursions during OGTTs. In particular, it may be higher than expected from fasting glucose, especially in East Asian populations in which progression to T2D is a consequence more of impaired secretion than insulin resistance. This discrepancy has been codifed as the Hemoglobin Glycation Index (HGI) by colleagues in Korea. In a cross-sectional study, they found that HGI was associated with prevalence of cardiovascular disease (Reference #2). In ongoing work, we continue using the model to extract more information from OGTTs and IVGTTs, with a goal of developing better tools to predict T2D risk.